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Introduction to Machine Learning

      Author: Delcan   |   20 October 2020   |   comments: 0

Introduction to Machine Learning Introduction to Machine Learning Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: aac, 44100 Hz Language: English | Size: 6.48 GB | Duration: 14.5 hours What you'll learn Introduction to Machine Learning: math, algorithms, and Python coding for Linear and Logistic Regression and Neural Networks Requirements Linear Algebra (matrix multiplication), Multivariable Calculus (gradients), Python programming Description Goal: Provide an introduction to machine learning focusing on linear and logistic regression and neural network approaches Course Covers: Underlying mathematics and algorithms in detail Development in Python of a machine learning framework emphasizing how algorithms translate into code Approaches for improving performance of machine learning systems Application to regression, binary and multi-class classification problems Case studies: house price prediction, spam classification, digits identification Tensorflow examples Course Approach Lecture videos with many examples to illustrate the theory Jupyter Notebook demos to complement lectures Walk through of development of machine learning framework and running of programs 50+ exercises (with solutions) including math problems, Jupyter notebook based exercises, and programming problems Github site with all course materials (course framework code, Jupyter notebook demos, exercises & solutions, pdf of presentations) Who this course is for: Students without any previous experience with machine learning Students with previous experience who would like to revisit the math, algorithms and coding for machine learning in detail https://www.udemy.com/course/introduction-to-machine-learning-using-python/
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